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Record W4402297877 · doi:10.1016/j.xkme.2024.100898

Dialysis Modality Education Timing and Home Dialysis Uptake: A Quality Improvement Study

2024· article· en· W4402297877 on OpenAlexafffundabout
Desheng Lu, M Akhtar, Lisa Dubrofsky, Bourne L. Auguste

Bibliographic record

VenueKidney Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreWomen's College HospitalUniversity of Toronto
FundersTemerty Faculty of Medicine, University of Toronto
KeywordsHome dialysisDialysisModality (human–computer interaction)MedicineQuality (philosophy)Intensive care medicineInternal medicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Rationale & Objective Investigating the effect of a quality improvement intervention aimed at enhancing the choice of home dialysis among patients through improved educational sessions on dialysis modalities. Study Design A new referral protocol initiated on September 15, 2022, sought to direct patients with advanced kidney disease to modality education sessions. This protocol involved an updated referral form and process, requiring nephrologists to refer patients with an estimated glomerular filtration rate below 15mL/min/1.73m 2 or specified Kidney Failure Risk Equation scores to modality educators for education. The impact was measured by the uptake of the education and the choice of home dialysis by patients. Setting & Participants The study took place at Sunnybrook Health Sciences Centre in Toronto, Canada, involving 532 patients across 1,723 clinical encounters from October 2019 to June 2023. Predictor The intervention was predicted to lead to an increase in both the number of patients receiving modality education and those choosing home dialysis. Outcomes The primary outcome measured was the selection of home dialysis following modality education, with a secondary focus on the proportion of patients educated post intervention. Analytical Approach Statistical process charts were used for monitoring changes in education uptake and home dialysis selection rates following the intervention. Results After implementing the standardized referral system, the proportion of patients receiving modality education increased from 27.1%-56.7%. However, the rate of selecting home dialysis remained constant at 50.9%. Overall home dialysis prevalence at our center averaged 19.6%, remaining lower than the provincial average of 24.4% by the end of the study period. Limitations The study was limited to 1 center, without evaluating patient satisfaction or dissecting the complexity of educational content and delivery. Conclusions We succeeded in boosting education rates but failed to achieve higher home dialysis choice rates, possibly owing to the complexity involved in modality choices. We plan to further investigate the factors influencing patient choices during modality education to better promote home dialysis selection. Plain-Language Summary The study focused on whether teaching patients more about their dialysis options would encourage them to choose home dialysis. A new system was introduced at an academic hospital in Toronto, requiring doctors to refer patients with advanced kidney disease to educational sessions. The aim was to see if patients who learned more about dialysis would be more likely to manage their treatment at home. The result was more patients received these educational sessions, but this did not lead to more of them choosing home dialysis. Future research must investigate what other factors influence patients' decisions to consider dialysis treatments at home.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.800

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.352
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes3
Has abstractyes

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